Understanding the planning of LLM agents: A survey
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866917584492822528 |
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| author | Huang, Xu Liu, Weiwen Chen, Xiaolong Wang, Xingmei Wang, Hao Lian, Defu Wang, Yasheng Tang, Ruiming Chen, Enhong |
| author_facet | Huang, Xu Liu, Weiwen Chen, Xiaolong Wang, Xingmei Wang, Hao Lian, Defu Wang, Yasheng Tang, Ruiming Chen, Enhong |
| contents | As Large Language Models (LLMs) have shown significant intelligence, the progress to leverage LLMs as planning modules of autonomous agents has attracted more attention. This survey provides the first systematic view of LLM-based agents planning, covering recent works aiming to improve planning ability. We provide a taxonomy of existing works on LLM-Agent planning, which can be categorized into Task Decomposition, Plan Selection, External Module, Reflection and Memory. Comprehensive analyses are conducted for each direction, and further challenges for the field of research are discussed. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_02716 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Understanding the planning of LLM agents: A survey Huang, Xu Liu, Weiwen Chen, Xiaolong Wang, Xingmei Wang, Hao Lian, Defu Wang, Yasheng Tang, Ruiming Chen, Enhong Artificial Intelligence Computation and Language Machine Learning As Large Language Models (LLMs) have shown significant intelligence, the progress to leverage LLMs as planning modules of autonomous agents has attracted more attention. This survey provides the first systematic view of LLM-based agents planning, covering recent works aiming to improve planning ability. We provide a taxonomy of existing works on LLM-Agent planning, which can be categorized into Task Decomposition, Plan Selection, External Module, Reflection and Memory. Comprehensive analyses are conducted for each direction, and further challenges for the field of research are discussed. |
| title | Understanding the planning of LLM agents: A survey |
| topic | Artificial Intelligence Computation and Language Machine Learning |
| url | https://arxiv.org/abs/2402.02716 |